Search results for: strategic spiritual intelligence

Authors: Samir Hessas

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Modern medicine is witnessing a profound transformation as advanced technology reshapes surgical environments. Hybrid operating rooms, where state-of-the-art medical equipment, advanced imaging solutions, and Artificial Intelligence (AI) converge, are at the forefront of this revolution. In this comprehensive exploration, we scrutinize the multifaceted facets of AI and delve into an array of groundbreaking technologies. We also discuss visionary concepts that hold the potential to revolutionize hybrid operating rooms, making them more efficient and patient-centered. These innovations encompass real-time imaging, surgical simulation, IoT and remote monitoring, 3D printing, telemedicine, quantum computing, and nanotechnology. The outcome of this fusion of technology and imagination is a promising future of surgical precision, individualized patient care, and unprecedented medical advances in hybrid operating rooms.

Keywords: artificial intelligence, hybrid operating rooms, telemedicine, monitoring

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Authors: Jorge Duarte de Sá

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The appearance of the new media technologies has opened new fields of intervention in architecture creating a new dynamic communication in the relationship between public and space, where are present technological devices that enable a new sensory experience, aesthetic and even spiritual. This connection makes relevant the idea of rehabilitate architectonic spaces with new media technologies such as sacred spaces. This research aims to create a media project integrated in sacred spaces that combine Architecture, Art and New Technologies, exploring new perspectives and different dynamics in space.

Keywords: media, architecture, religious spaces, projections, contemplation

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Franco Ceasar Agbalog, Shintaro Yukawa

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Mindfulness is increasingly being used as a method for resolving conflict. However, less is known about how its positive outcome develops. To better understand the underlying effects of mindfulness on conflict resolution strategies, this study examines the potential mediating factors between them. The researchers hypothesized that Emotional Intelligence (EI) mediates the effects of mindfulness on conflict resolution strategies due to its similar components to the benefits of mindfulness, such as awareness and control of one’s emotions, awareness and understanding of other’s emotions, and cultivation of compassion and empathy. Using a random sampling, 157 participants completed three questionnaires: Five Facet Mindfulness Questionnaire (FFMQ), Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), and Rahim Organizational Conflict Inventory-II (ROCI-II). Utilizing the SPSS Process, results showed a significant relationship between mindfulness and EI. However, among the five approaches to conflict resolution, only the integrating style was significantly related to EI. Following the principle of Mediation Analysis, mindfulness has an indirect effect on integrating style. Moreover, mindfulness and conflict resolution strategies were not significantly related. This is a rather surprising result because research literature has always indicated a positive relationship between the two variables. These findings imply that although integrating style is generally considered the best approach in handling conflict, each style may be appropriate depending on the situation. Mindfulness allows practitioners to have a holistic view of the conflict situation and choose the approach they think best for that specific situation. This could explain why statistically, there is no direct effect of mindfulness on conflict resolution strategies. This work provides basis for the necessity to investigate the factors of conflict instead of the conflict resolution strategies; factors that can be manipulated and may be directly influenced by mindfulness.

Keywords: conflict resolution strategies, emotional intelligence, mindfulness and conflict, ROCI-II integrating style

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Authors: Ramon F. B. da Silva, Mateus Batistella, Emilio Moran

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Although the existence of two Forest Transition (FT) pathways, the economic development and the forest scarcity, there are many contexts that shape the model of FT observed in each particular region. This means that local conditions, such as relief, soil quality, historic land use/cover, public policies, the engagement of society in compliance with legal regulations, and the action of enforcement agencies, represent dimensions which combined, creates contexts that enable forest regeneration. From this perspective we can understand the regeneration process of native vegetation cover in the Paraíba Valley (Forest Atlantic biome), ongoing since the 1960s. This research analyzed public information, land use/cover maps, environmental public policies, and interviewed 17 stakeholders from the Federal and State agencies, municipal environmental and agricultural departments, civil society, farmers, aiming comprehend the contexts behind the forest regeneration in the Paraíba Valley, Sao Paulo State, Brazil. The first policy to protect forest vegetation was the Forest Code n0 4771 of 1965, but this legislation did not promote the increase of forest, just the control of deforestation, not enough to the Atlantic Forest biome that reached its highest pick of degradation in 1985 (8% of Atlantic Forest remnants). We concluded that the Brazilian environmental legislation acted in a strategic way to promote the increase of forest cover (102% of regeneration between 1985 and 2011) from 1993 when the Federal Decree n0 750 declared the initial and advanced stages of secondary succession protected against any kind of exploitation or degradation ensuring the forest regeneration process. The strategic policy formulation was also observed in the Sao Paulo State law n0 6171 of 1988 that prohibited the use of fire to manage agricultural landscape, triggering a process of forest regeneration in formerly pasture areas.

Keywords: forest transition, land abandonment, law enforcement, rural economic crisis

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Authors: Monday Dickson

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Shortly before the end of the second world war, allied leaders and other western powers designed an economic regime that would foster, among other things, global economic reconstruction, prosperity and overall development of countries of the world. They founded both the World Bank and the International Monetary Fund (IMF), with a general consensus that while the latter should specialize in monitoring global and national economies and acting as a lender of last resort, the former should focus on fighting poverty and promoting development. In setting the rules for world trade, the General Agreement on Trade and Tariffs (GATT) evolved into the World Trade Organisation (WTO). This paper, therefore, examines the impact of the activities of these institutions on the transformation and development aspirations of countries of the Third World. The study adopts the descriptive and analytical methods of investigation and derived relevant secondary data from books, journal articles, encyclopedia as well as reports from countries of the Third World. Findings show that rather than fostering poverty reduction and overall development as envisaged, the activities of global economy system leads to the “development of underdevelopment” of the Third World Countries. The strategic options that are available to countries of the Third World derived from the ability of the national governments to develop programmes of systematic exploration and exploitation of vital indices of relations with strategic countries to advance their development agenda.

Keywords: development, global economic system, prosperity, third world

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Angela Oktavia Suryani, Bernadeth Gloria, Edwin Sutamto, Jessica Kristianty, Ni Made Rai Sapitri, Patricia Catherine Agla, Sitti Arlinda Rochiadi

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It was found that some blogs or personal websites in Indonesia sell standardized intelligence tests (for example, Progressive Matrices (PM), Intelligence Structure Test (IST), and Culture Fair Intelligence Test (CFIT)) and other psychological tests, together with the manual and the key answers for public. Individuals can buy and prepare themselves for selection or recruitment with the real test. This action drives people to lie to the institution (education or company) and also to themselves. It was also found that those tests are old. Some items are not relevant with the current context, for example a question about a diameter of a certain coin that does not exist anymore. These problems motivate us to develop a new intelligence battery test, namely of Multiple Aptitude Battery (MAB). The battery test was built by using Thurstone’s Primary Mental Abilities theory and intended to be used by high schools students, university students, and worker applicants. The battery tests consist of 9 subtests. In the current study we examine six subtests, namely Reading Comprehension, Verbal Analogies, Numerical Inductive Reasoning, Numerical Deductive Reasoning, Mechanical Ability, and Two Dimensional Spatial Reasoning for university students. The study included 1424 data from students recruited by convenience sampling from eight faculties at Atma Jaya Catholic University of Indonesia. Classical and modern test approaches (Item Response Theory) were carried out to identify the item difficulties of the items and confirmatory factor analysis was applied to examine their internal validities. The validity of each subtest was inspected by using convergent–discriminant method, whereas the reliability was examined by implementing Kuder–Richardson formula. The result showed that the majority of the subtests were difficult in medium level, and there was only one subtest categorized as easy, namely Verbal Analogies. The items were found homogenous and valid measuring their constructs; however at the level of subtests, the construct validity examined by convergent-discriminant method indicated that the subtests were not unidimensional. It means they were not only measuring their own constructs but also other construct. Three of the subtests were able to predict academic performance with small effect size, namely Reading Comprehension, Numerical Inductive Reasoning, and Two Dimensional Spatial Reasoning. GPAs in intermediate level (GPAs at third semester and above) were considered as a factor for predictive invalidity. The Kuder-Richardson formula showed that the reliability coefficients for both numerical reasoning subtests and spatial reasoning were superior, in the range 0.84 – 0.87, whereas the reliability coefficient for the other three subtests were relatively below standard for ability test, in the range of 0.65 – 0.71. It can be concluded that some of the subtests are ready to be used, whereas some others are still need some revisions. This study also demonstrated that the convergent-discrimination method is useful to identify the general intelligence of human.

Keywords: intelligence, psychometric examination, multiple aptitude battery, university students

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Authors: Chen Xi, LIU Xuebin, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Lao Xuerui

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Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature have led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using Yolov5 recognition technology) and recording and managing them in a database.

Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network, machine vision

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Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Preventing abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep, long short-term memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviors far from the expected one depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behavior analysis, LSTM

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Authors: Ke Ma

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Through the long course of history, Buddhism has captivated generations of brilliant minds with its enlightening but elusive discernment. Far from religious dogmas, Buddhism not only represents spiritual revelation, but also logical reasoning.Among all of Buddhism’s concepts, emptiness is the most famous, and abstruse one. This word resulted from an inaccurate translation confuses both Buddhists and religious scholars who understand Heart Sutra based on its English version. In this essay, the idea of “emptiness” will be reinterpreted as “information,” leading not only to a clarification of the ideology of Buddhism, but also to greater correspondence between Buddhism concepts and cognitive science.

Keywords: religion, cognitive science, psychology, Buddhism

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Authors: Mai Anh Tuan, Wenlong Liu, Meng Li

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Despite warnings and concerns about the use of fast food that has health effects, the fast-food industry is actually a source of profit for the global food industry. Obviously, in the face of such huge economic benefits, investors will not hesitate to continuously add recipes, processing methods, menu diversity, etc., to improve and apply information technology in enhancing the diners' experience; the ultimate goal is still to attract diners to find their brand and give them the fastest, most convenient and enjoyable service. In China, as the achievements of the industrial revolution 4.0, big data and artificial intelligence are reaching new heights day by day, now fast-food diners can instantly pay the bills only by identifying the biometric signature available on the self-ordering kiosk, using their own face without any additional form of confirmation. In this study, the author will evaluate the acceptance level of customers with this new form of payment through a survey of customers who have used and witnessed the use of smart kiosks and biometric payments within the city of Nanjing, China. A total of 200 valid volunteers were collected in order to test the customers' intentions and feelings when choosing and experiencing payment through AI services. 55% think that it bothers them because of the need for personal information, but more than 70% think that smart kiosk brings out many benefits and convenience. According to the data analysis findings, perceived innovativeness has a positive influence on satisfaction which in turn affects behavioral intentions, including reuse and word-of-mouth intentions.

Keywords: artificial intelligence, catering industry, smart kiosks, technology acceptance

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Authors: Kholil Kholil, Soecahyadi Soecahyadi

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Geographically, Padang Panjang Regency which located in the heart of Western Sumatra has great potentials for the tourism industry. However, these potentials have not been strategically developed for increasing local economic development and people's welfare. The purpose of this research is to design the strategy of sustainable tourism area development using Strategic Assumption Surfacing and Testing (SAST) and Exponential Rank Method (ERM). Result study showed, there are four aspects which importance and certainly for developing tourism area destination in Padang Panjang Regency; (1) tourist information center and promotion, (2) regional cooperation development; (3) minangese center as a center of excellence; and (4) building the center of the public market. To build an attractive tourist area required action plan includes the construction of an information center, center of excellence of minangese, and tourist infrastructure; and public participation is a key success factor for ensuring sustainability of tourism development in Padang Panjang Regency.

Keywords: local economic development, tourism attraction, SAST, ERM

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Authors: Supranee Wattanasin

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This research study was a qualitative documentary research by using an in-depth interview with many experts in the field who has both knowledge and experience to provide information to create a strategic plan to enhance the students’ ethics. The findings revealed that there were five areas that require an attention. The five areas included honesty, accurate fact, human right, speed, and responsibility. The development of the strategic plan to enhance the ethics for students who major in communication arts can be concluded as follows. First, the government, private, and religion sectors need to come up together and set up the activities to promote the ethical standard in schools, universities, and organizations. Second, it is important to cultivate the knowledge that ethics is important of the professional jobs, especially in the mass communication and media. Third, the Philosophy of Sufficiency Economy should be brought to explain to students in order for them to have some immunity to the negative attitude such as drinking alcohol, gambling, cut classes, and cheating at exams. Fourth, experts in the field of ethics should be found to provide more knowledge to students and allow students to participate in activities that will increase their experience and knowledge of the real world problem.

Keywords: communication arts, ethics, mass communication, media, strategy

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Authors: Josie Gardner

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The overall intention of this research is to reimagine peacebuilding in both in theory and practical application in light of the shortcomings and unsustainability of the current peacebuilding paradigm. These limitations are identified here as an overly rational-material approach to peacebuilding that neglects the inner dimension of peace for a fragmented rather than holistic model, and that espouses a conflict and violence-centric approach to peacebuilding. In counter, this presentation is purposed to investigate the dynamics of inner and outer peace as a holistic, complex system towards ‘inner-outer’ peacebuilding. This paper draws from primary research in the protracted conflict context of north-western India (Jammu, Kashmir & Ladakh) as a case study. This presentation has two central aims. First, to introduce the process of inner (psycho-spiritual) peacebuilding, which has thus far been neglected by mainstream and orthodox literature. Second, to examine why inner peacebuilding is essential for realising sustainable peace on a broader scale as outer (socio-political) peace and to better understand how the inner and outer dynamics of peace relate and affect one another. To these ends, Josephine (the researcher/author/presenter) partnered with Yakjah Reconciliation and Development Network to implement a series of action-oriented workshops and retreats centred around healing, reconciliation, leadership, and personal development for the dual purpose of collaboratively generating data, theory, and insights, as well as providing the youth leaders with an experiential, transformative experience. The research team created and used a novel methodological approach called Mapping Ritual Ecologies, which draws from Participatory Action Research and Digital Ethnography to form a collaborative research model with a group of 20 youth co-researchers who are emerging youth peace leaders in Kashmir, Jammu, and Ladakh. This research found significant intra- and inter-personal shifts towards an experience of inner peace through inner peacebuilding activities. Moreover, this process of inner peacebuilding affected their families and communities through interpersonal healing and peace leadership in an inside-out process of change. These insights have generated rich insights and have supported emerging theories about the dynamics between inner and outer peace, power, justice, and collective healing. This presentation argues that the largely neglected dimension of inner (psycho-spiritual) peacebuilding is imperative for broader socio-political (outer) change. Changing structures of oppression, injustice, and violence—i.e. structures of separation—requires individual, interpersonal, and collective healing. While this presentation primarily examines and advocates for inside-out peacebuilding and social justice, it will also touch upon the effect of systems of separation on the inner condition and human experience. This research reimagines peacebuilding as a holistic inner-outer approach. This offers an alternative path forward those weaves together self-actualisation and social justice. While contextualised within north-western India with a small case study population, the findings speak also to other conflict contexts as well as our global peacebuilding and social justice milieu.

Keywords: holistic, inner peacebuilding, psycho-spiritual, systems youth

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Authors: Idoia Landa Oregi, Itsaso Gonzalez Ochoantesana, Olatz Nicolas Buxens, Carlo Ferretti

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The impact of citizens in urban transformations has become increasingly important in the pursuit of creating citizen-centered cities. Citizens at the forefront of the urban transformation process are key to establishing resilient, sustainable, and inclusive cities that cater to the needs of all residents. Therefore, collecting data and information directly from citizens is crucial for the sustainable development of cities. Within this context, public participation becomes a pillar for acquiring the necessary information from citizens. Public participation in urban transformation processes establishes a more responsive, equitable, and resilient urban environment. This approach cultivates a sense of shared responsibility and collective progress in building cities that truly serve the well-being of all residents. However, the implementation of public participation practices often overlooks strategies to effectively engage citizens in the processes, resulting in non-successful participatory outcomes. Therefore, this research focuses on identifying and analyzing the critical aspects of citizen engagement during the same participatory urban transformation process in different European contexts: Ermua (Spain), Elva (Estonia) and Matera (Italy). The participatory neighborhood regeneration process is divided into three main stages, to turn social districts into inclusive and smart neighborhoods: (i) the strategic level, (ii) the design level, and (iii) the implementation level. In the initial stage, the focus is on diagnosing the neighborhood and creating a shared vision with the community. The second stage centers around collaboratively designing various action plans to foster inclusivity and intelligence while pushing local economic development within the district. Finally, the third stage ensures the proper co-implementation of the designed actions in the neighborhood. To this date, the presented results critically analyze the key aspects of engagement in the first stage of the methodology, the strategic plan, in the three above-mentioned contexts. It is a multifaceted study that incorporates three case studies to shed light on the various perspectives and strategies adopted by each city. The results indicate that despite of the various cultural contexts, all cities face similar barriers when seeking to enhance engagement. Accordingly, the study identifies specific challenges within the participatory approach across the three cities such as the existence of discontented citizens, communication gaps, inconsistent participation, or administration resistance. Consequently, key learnings of the process indicate that a collaborative sphere needs to be cultivated, educating both citizens and administrations in the aspects of co-governance, giving these practices the appropriate space and their own communication channels. This study is part of the DROP project, funded by the European Union, which aims to develop a citizen-centered urban renewal methodology to transform the social districts into smart and inclusive neighborhoods.

Keywords: citizen-centred cities, engagement, public participation, urban transformation

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Authors: Mizuno Norihito

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This study attempts to examine Japanese views of Thailand primarily in the 1920s and 1930s through the analysis of documents published by the Office of Governor-General of Taiwan (Taiwan Sotokufu) and its affiliated organizations. Japan regarded Taiwan, under its control since 1895, as a foothold to making inroads into the South, and The governor-general office was active in investigations and intelligence gathering in Southeast Asia, as well as the southern part of the Chinese continent. Documents published by the governor-general office and its related organizations, especially those in a couple of decades following the First World War, reveal that the Japanese paid attention to the presence of the-Thai-Chinese during the time period. It would not be surprising that the desiring to penetrating into the Thai market, as well as the markets of the rest of Southeast Asia, the Japanese could not ignore the presence of the Thai-Chinese because of their local economic influences. The increased Japanese concern about the Thai-Chinese toward the end of the 1920s and throughout the 1930s was, moreover, intertwined with the increased tension between China and Japan. In other words, Thailand, as well as the rest of Southeast Asia, became another arena of Sino-Japanese confrontation. The rise of nationalism against Japan in China infected the Thai-Chinese communities and threatened Japanese economic activities in the country. However, the Japanese simultaneously found out that Thai-Chinese concert with anti-Japanese in China did not necessarily match their business interests and that the Thai government’s efforts to assimilate the Thai-Chinese into the Thais society and strategic approach to Japan in the late 1930s hampered their anti-Japanese actions.

Keywords: Japanese-Thai Relations, Sino-Japanese relations, Thai Chinese, Overseas Japanese

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Authors: Lien Fa Lin, Yung Ming Li, Hsin Chen Hsieh

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The rise of smartphones brings new concept So-Lo-Mo (social-local-mobile) in mobile commerce area in recent years. However, current So-Lo-Mo services only focus on individual users but not a group of users, and the development of group commerce is not enough to satisfy the demand of real-time group buying and less to think about the social relationship between customers. In this research, we integrate mobile intelligence with group commerce and consider customers' preference, real-time context, and social influence as components in the mechanism. With the support of this mechanism, customers are able to gather near customers with the same potential purchase willingness through mobile devices when he/she wants to purchase products or services to have a real-time group-buying. By matching the demand and supply of mobile group-buying market, this research improves the business value of mobile commerce and group commerce further.

Keywords: group formation, group commerce, mobile commerce, So-Lo-Mo, social influence

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Authors: Niloofar Fathizaviyehkord

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Just as two hands cannot make a good boxer, knowing two or more languages cannot make a skillful interpreter. Interpreting, either consecutive or simultaneous, is a cognitively demanding task requiring not only linguistic and discourse knowledge but also strategic competence. Moreover, experience level can play a very crucial role in the strategies interpreters may employ since translation and interpretation quality is a matter of experience, besides other factors, as well. With regard to the significance of strategic competence, this study investigated what strategies are mainly employed by interpreters, what strategies are employed more frequently, and whether experience level can affect the choice of strategies by interpreters or not. To collect the necessary data, the first retrospective interviews were held with 20 interpreters experienced more or less in simultaneous and consecutive interpretation to see what strategies other than those classified in the literature are employed by interpreters. Then, several classifications of strategies in literature were merged with those emerging from the retrospective interviews to come up with a comprehensive questionnaire on interpreting strategies. After seeking five experts’ opinions regarding the wording/content of the questionnaire, it was given to 60 interpreters. The statistical analysis of the questionnaire data and experience level through ANOVA showed experience level could affect the choice of strategies. This study closes with the theoretical/practical implications of the findings for interpreter training.

Keywords: experience level, consecutive and simultaneous, interpretation strategies, translation

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Authors: Walid Moudani, Ahmad Shahin

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This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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Authors: Arkaprabha Bhattacharyya, Makarand Hastak

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The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.

Keywords: economic growth, infrastructure development, infrastructure projects, strategic investment

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Authors: Abdulmalek Ahmed

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Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%).

Keywords: Artificial Intelligence (AI), Formation pressure, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Networks (FN), Radial Basis Function (RBF)

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Authors: Norazilawati Binti Md Dahlal, Nabiila Binti Mat Yusoff, Anis Najiha Binti Ahmad

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With the increasing demand for halal products, there is a growing emphasis on ensuring their quality and adherence to halal standards. However, the vulnerability of halal goods to fraud and adulteration poses a significant challenge to the integrity of the halal industry. Whistleblowers play a pivotal role in safeguarding the safety and integrity of halal food by exposing wrongdoings, misconduct, and fraudulent practices. This study explores the implementation of whistleblowing practices aligned with halal and toyyib principles to effectively address halal food fraud issues. Whistleblowing is defined as the act of disclosing information about misconduct, immorality, or unlawful activities to relevant authorities or the public. Although whistleblowing is universally recognized as beneficial, it exposes whistleblowers to substantial risks, including career setbacks, reputation damage, and personal safety threats. Despite legal protections, whistleblowers often face retaliation and hesitancy to come forward. By integrating the principles of halal and toyyib, which encompass the physical and spiritual as well as material and supernatural elements, effective whistleblowing practices can be developed. These principles include the physical characteristic of the product in accordance with Shari’ah law (P1); products that are sourced ethically and responsibly (P2); Products that meet high standard of quality and safety (P3); functioning as servant and caliph of Allah in managing according to Allah's commands and prohibitions (P4); not excessively wasteful or extravagant (P5); positive moral and spiritual implications associated with the product (P6); and aimed at achieving prosperity in both this life and the Hereafter (P7). Employing a quantitative research approach, this study examines Islamic primary data sources and secondary data sources to investigate the prevalence and impact of whistleblowing in the halal industry. By analyzing the principles of halal and toyyib and exploring the importance of whistleblowing effective whistleblowing practices, this research aims to enhance our understanding of promoting accountability and justice within the halal industry from an Islamic perspective.

Keywords: whistleblowing, halal and toyyib, food fraud, halal integrity, Islamic practices

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Authors: Charintorn Suwannawong, Tananpon Yavilas, Sopida Boonaneksap, Chotika Viriyarattanasak, Chairath Tangduangdee

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With increasing aging population and health conscious consumers, the demand for health promoting products such as functional foods, dietary supplements, and nutraceutical products has continuously increased in Thailand. Nevertheless, the strategic framework for regulatory functional food developments in Thailand is still unclear. The objective of this study was to survey stakeholders’ perspectives on three scopes, consisting of 1) the current status 2) obstacles, and 3) future trend for the development and production of functional foods in Thailand. A survey was conducted by interviewing ten experts from governmental organization, industrial sector and academic institute. The obtained results show that there is no established definition for functional foods in Thailand. There is a variety of raw materials that are capable to be potential ingredients for functional food production in Thailand and exported to global market. However, the scaling up technology into a commercial production is limited. Moreover, there is a need to establish the infrastructures, such as testing laboratory, and regulatory standards for quality control and ensuring product safety. This information is useful for government in the development of the strategic framework and policy statement on improvement of functional food industry in Thailand.

Keywords: functional foods, interview, perspective, Thailand

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Authors: Wendy de Gomez

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Standardization is a critical element in the ability of a society to reduce uncertainty, subjectivity, misrepresentation, and interpretation while simultaneously contributing to innovation. Technological standardization is critical to codify specific operationalization through legal instruments that provide rules of development, expectation, and use. In the current emerging technology landscape Artificial Intelligence (AI) hardware as a general use technology has seen incredible growth as evidenced from AI technology patents between 2012 and 2018 in the United States Patent Trademark Office (USPTO) AI dataset. However, as outlined in the 2023 United States Government National Standards Strategy for Critical and Emerging Technology the codification through standardization of emerging technologies such as AI has not kept pace with its actual technological proliferation. This gap has the potential to cause significant divergent possibilities for the downstream outcomes of AI in both the short and long term. This original empirical research provides an overview of the standardization efforts around AI in different geographies and provides a background to standardization law. It quantifies the longitudinal trend of Artificial Intelligence hardware patents through the USPTO AI dataset. It seeks evidence of existing Standard Essential Patents from these AI hardware patents through a text analysis of the Statement of patent history and the Field of the invention of these patents in Patent Vector and examines their determination as a Standard Essential Patent and their inclusion in existing AI technology standards across the four main AI standards bodies- European Telecommunications Standards Institute (ETSI); International Telecommunication Union (ITU)/ Telecommunication Standardization Sector (-T); Institute of Electrical and Electronics Engineers (IEEE); and the International Organization for Standardization (ISO). Once the analysis is complete the paper will discuss both the theoretical and operational implications of F/Rand Licensing Agreements for the owners of these Standard Essential Patents in the United States Court and Administrative system. It will conclude with an evaluation of how Standard Setting Organizations (SSOs) can work with SEP owners more effectively through various forms of Intellectual Property mechanisms such as patent pools.

Keywords: patents, artifical intelligence, standards, F/Rand agreements

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Authors: Alfredo R. Roa-Henriquez

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This paper is about organizational-level resilience and decision-making in the face of natural hazards. Research on resilience emerged to explain systems’ ability to absorb and recover in the midst of adversity and uncertainty from natural disasters, crises, and other disruptive events. While interest in resilience has accelerated, research multiplied, and the number of policies and implementations of resilience to natural hazards has increased over the last several years, mainly at the level of communities and regions, there has been a dearth of empirical work on resilience at the level of the firm. This paper uses empirical data and a sample selection model to test some hypotheses related to the firm’s dependence on critical resources, the sharing of resources and its economic resilience. The objective is to understand how the sharing of resources among organizations is related to economic resilience. Empirical results that are obtained from a sample of firms affected by Superstorm Sandy and Hurricane Harvey indicate that there is unobserved heterogeneity that explains the strategic behavior of firms in the post-disaster and that those firms that are more likely to resource share are also the ones that exhibit higher economic resilience. The impact of property damage on the sharing of resources and economic resilience is explored.

Keywords: economic resilience, resource sharing, critical resources, strategic management

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Authors: Serge Lacroix

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The proposed study looks at the psychoeducational assessment of bilingual students, in English and French in this case. It will be the opportunity to look at language of assessment and specifically how certain tests can be administered in one language and others in another language. It is also a look into the questioning of the validity of the test scores that are obtained as well as the quality and generalizability of the conclusions that can be drawn. Bilingualism and multiculturalism, although in constant expansion, is not considered in norms development and remains a poorly understood factor when it is at play in the context of a psychoeducational assessment. Student placement, diagnoses, accurate measures of intelligence and achievement are all impacted by the quality of the assessment procedure. The same is true for questionnaires administered to parents and self-reports completed by bilingual students who, more often than not, are assessed in a language that is not their primary one or are compared to monolinguals not dealing with the same challenges or the same skills. Results show that students, when offered to work in a bilingual fashion, chooses to do so in a significant proportion. Recommendations will be offered to support educators aiming at expanding their skills when confronted with multilingual students in an assessment context.

Keywords: psychoeducational assessment, bilingualism, multiculturalism, intelligence, achievement

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Authors: Jae Ni Jang, Young Uk Kim

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Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

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Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

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Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu

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In this study, an artificial intelligence-based (ANN based) analytical method has been developed for analyzing earthquake performances of the reinforced concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code- 2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

Keywords: artificial intelligence, earthquake, performance, reinforced concrete

Procedia PDF Downloads 448